There are two Global Navigation Satellite Systems (GNSS) which have been fully deployed for a number of years (the US Global Positioning System and the Russian GLONASS) and two more which are under deployment (the Chinese Beidou Navigation Satellite System and the European Galileo system). These systems rely on the same principles: microwave radio frequency (RF) signals are broadcast from a number of satellites which orbit; the signals carry a PRN (Pseudo Random Noise) code which is correlated with a local replica in a receiver configured to receive the broadcast signals; when a receiver is capable of acquiring and tracking signals from a satellite, its processing capabilities demodulate the code signal using the correlation process, and calculate a pseudo-range, which is the distance between the receiver and the satellite. This pseudo-range is taken in combination with pseudo-range acquired from other satellites (generally four, or three when the altitude estimate is not needed) to determine a position, velocity and time (PVT).
Positioning messages are usually made of a navigation message, comprising information including the satellites' position, ephemerides, and the message transmission time. The navigation message is further modulated by a PRN (Pseudo Random Noise) code with each satellite using a distinct PRN code, so that the GNSS receivers can isolate the signal originating from one particular satellite. These signals usually use a BPSK (Binary Shift Keying) or a BOC (Binary Offset Carrier) modulation, depending on accuracy and spectral occupation considerations.
However, depending on the propagation environment, the signal received by a GNSS receiver from one satellite may result from the combination of Line Of Sight (LOS) and Non Line of Sight (NLOS) paths of the signal, the LOS path being the direct propagation path between the satellite and the receiver, and the NLOS paths the results of reflections occurring. The NLOS signals are delayed replicas of the LOS signal, with a potentially different amplitude and phase, the delay being a function of the difference of distance between the direct propagation path and the reflected propagation path. Multipath reflections are particularly present when the GNSS receiver operates in an urban or indoor environment.
The NLOS components of such a multipath signal create artifacts in the composite correlation function of the received signal, which is used to synchronize the receiver and determine a pseudo range with the satellite. The artifacts decrease the quality of the synchronization position determined, and thus affect the quality of the overall estimate. As a result, the accuracy of the positioning will tend to be worse in urban environment than in rural environment (where trees are not present), while this is where a high accuracy is required.
In addition, the signal received by a GNSS receiver comprises at the same time the signal and associated multipath reflections transmitted by all the satellites in sight, which further complicates the reception process.
Different techniques are known to deal with the issue of detecting and correcting multipath reflections in a received signal. Among these techniques are the equalization techniques (linear equalization, decision feedback equalizer, adaptive filter, Viterbi equalizer, Rake receiver . . . ), aiming at combining the NLOS components of the received signal with the LOS component. However, these techniques are not necessarily adapted to equalize a spread spectrum signal operating at low SNR (acronym for Signal over Noise Ratio), and may require a learning phase in order to characterize the propagation channel, which increases the time required to lock a position, and thus may not be compatible with a receiver moving in an urban environment because, in that case, the propagation channel changes quickly. In addition, when based on an estimation of the propagation channel, these techniques are not suited to perform this estimation when the received signal is a combination of various signals originating from different transmitters.
U.S. Pat. No. 6,031,882 describes various methods to estimate the characteristics of the propagation channel and mitigate multiple propagation paths.
Among these methods is a first method, called “slope transition method”, which determines the delay of the multipath reflections by analyzing the slope of the output of the correlation function between the received signal and a local replica of the signal. The complex gain of each multiple path is then estimated using a least square method between the received signal and a reconstructed multipath signal. Knowing their respective delays and complex amplitudes, the multipath reflections can be suppressed from the received signal. This method suffers from the lack of precision of the slope transition analysis when the noise level is high, and requires a high processing power to determine the amplitudes of the reflected propagation paths.
A second method described in the above referenced US patent is called the “cepstrum processing approach”, wherein the delays of the various paths are estimated performing a complex cepstrum transform on the received signal, the cepstrum transform being the inverse Fourier transform of the log-magnitude Fourier spectrum. The path delays can be directly determined from the result of this transform. The complex gain of the various paths are then estimated using a least square method between the received signal and a reconstructed multipath signal, in order to remove the multipath reflections from the received signal. This method still requires a high processing power to determine the complex gain of the multipath reflections, and is not adapted when the received signal is the sum signal originating from different satellites, each signal having its own multiple paths, as the cepstrum transform will mix reflections occurring on the signal of interest, and reflections occurring on the other positioning signals.
Another multipath estimation technique is called the Multipath Estimating Delay Lock Loop (MEDLL). This technique is described in N. Delgado, F. Nunes, “Theoretical Performance of the MEDLL Algorithm for the New Navigation Signals, 7th conference on Telecommunications, 2009. The MEDLL algorithm estimates the amplitude, delay and phase of each multipath component using a maximum likelihood criteria from the output of a correlation function between the received signal and a local replica of the signal. The various paths of the received signal are estimated one by one iteratively: the direct path is estimated from the maximum of the correlation result, and its contribution subtracted from the output of the correlation. Then the multipath having the highest power level can be estimated and subtracted, and so on. When a given number of multiple paths are detected, their contributions are removed from the output of the correlation result, so that it only comprises the LOS path The MEDLL algorithm shows good theoretical results, but requires a high processing power and the knowledge of the total number of multiple paths, or specific criteria to stop iterating the multiple path detections.
There is accordingly a need for estimating and mitigating the multipaths signals with low processing computation at the correlation step.